Automated machine learning model identifies patients at risk for surgical complications

One of the main causes of death worldwide in the first 30 days following surgery is complications. Prior to the pandemic, heart disease and stroke were the leading causes of mortality, followed by surgical complications. Due to the circumstance, methods to identify surgical candidates who run the danger of joining the 4.2 million people worldwide who pass away within 30 days of an operation are now necessary. According to a study released on Friday in JAMA Network Open, scientists and medical professionals from the University of Pittsburgh have created an automated machine learning model that can recognize individuals who are at a high risk for complications following surgery.